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Generalized complexity pursuit

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, we study the blind source separation (BSS) problem of temporally correlated signals via exploring the nonlinear temporal structure and high-order statistics of source signals. A BSS method based on the nonlinear predictability of original sources is proposed, which extends linear coding complexity used by the original complexity pursuit to nonlinear coding complexity. Simulations by non-stationarity sources verify the efficient implementation of the proposed method, especially its robustness to the outliers.

Original languageEnglish
Title of host publicationProceedings - 4th International Conference on Natural Computation, ICNC 2008
Pages199-203
Number of pages5
DOIs
StatePublished - 2008
Event4th International Conference on Natural Computation, ICNC 2008 - Jinan, China
Duration: 18 Oct 200820 Oct 2008

Publication series

NameProceedings - 4th International Conference on Natural Computation, ICNC 2008
Volume3

Conference

Conference4th International Conference on Natural Computation, ICNC 2008
Country/TerritoryChina
CityJinan
Period18/10/0820/10/08

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